Legrand Logo

Legrand

Sr. AI Engineer

Posted 2 Hours Ago
In-Office or Remote
Hiring Remotely in United States
Senior level
In-Office or Remote
Hiring Remotely in United States
Senior level
Build and operate enterprise AI solutions, including agentic workflows, RAG pipelines, LLM integrations, and system connectors. Develop Python and FastAPI services, deploy and manage AI applications in Azure, implement security and monitoring practices, and contribute to architecture, code reviews, integrations, and technical planning. Collaborate with engineering, infrastructure, security, and business stakeholders while supporting scalable, maintainable AI platforms.
The summary above was generated by AI

Legrand has an exciting opportunity for an Sr. AI Engineer to join our Growing AI Team within Legrand North and Central America. This is a remote position.

Our AI team builds and operates MAIA - Legrand's internal AI assistant platform - along with an expanding portfolio of AI-powered automation and integration solutions across LNCA's subsidiaries. As an AI Engineer, you will contribute to day-to-day technical execution and support solution architecture - working in close collaboration with the Director of Generative AI to ensure solutions are secure, scalable, and built to last.

This role is the right fit for a technically exceptional engineer who wants to build high-quality AI solutions, contribute strong engineering judgment, and grow technical depth over time.

Responsibilities

Solution Architecture & Technical Ownership

  • Collaborate with the Director of Generative AI to design end-to-end AI solution architectures - including agentic workflows, RAG pipelines, LLM integrations, and enterprise system connectors - and own support the technical execution of those designs.
  • Develop and implement technical solutions for assigned use cases in alignment with established architecture, standards, and design guidance.
  • Evaluate Azure platform services and select appropriate hosting, storage, and compute patterns (Web Apps, Function Apps, CosmosDB, Container Registry, AI Search, Key Vault, and others) for each solution's specific requirements.
  • Follow established engineering standards for code structure and quality, security and access control, testing and validation, deployment practices, and technical documentation - building on the foundation established by the Director of Generative AI.

Deployment, Operations & Security

  • Support the deployment, configuration, and operational management of AI services in Microsoft Azure, ensuring solutions meet enterprise security requirements including private networking, role-based access control, and secrets management.
  • Proactively monitor deployed services, address performance or reliability issues, and maintain documentation to support long-term maintainability and team knowledge continuity.
  • Partner with IT, infrastructure, and security stakeholders to ensure solutions align with Legrand's enterprise architecture and compliance standards.

Development

  • Contribute hands-on development work on priority projects - particularly back-end services, agentic framework implementations, and complex API integrations.
  • Build, review, and maintain Python-based services (FastAPI), automation workflows, and integration pipelines; work across the stack as needed including front-end components (React/Vite/Chakra UI) and Node.js integrations.
  • Participate in code reviews and provide technical feedback to support quality, maintainability, and shared engineering practices.

Team Collaboration & Technical Support

  • Collaborate with the AI development team to clarify technical requirements, resolve development blockers, and support delivery of assigned work.
  • Participate in agile practices, including sprint planning, standups, and retrospectives, to support team clarity, shared context, and delivery momentum.
  • Share technical knowledge with teammates through pair programming, code review, and collaborative problem-solving.
  • Escalate complex technical issues appropriately and contribute to resolution planning with senior technical stakeholders.

Cross-Functional Collaboration

  • Support the AI-assisted solution refinement process by helping maintain clear work items in Azure DevOps and identifying opportunities to improve development workflows in partnership with the Director of Generative AI and AI Program Manager.
  • Support the AI Program Director and Director of Generative AI in assessing technical feasibility, effort estimation, and risk identification for proposed use cases.
  • Communicate technical decisions and architectural tradeoffs clearly to both technical peers and non-technical stakeholders.
Qualifications

Education:

  • Bachelor's or advanced degree in Computer Science, Software Engineering, or a related technical field. Equivalent professional experience in lieu of formal degree will be considered.

Experience:

  • 6+ years of professional software engineering experience, with at least 3 years focused on AI/ML development or enterprise AI system implementation.

Skills & Qualifications:

  • Strong proficiency in Python, including back-end service development with FastAPI, REST API design and integration, and automation scripting.
  • Hands-on, production experience deploying and managing cloud-hosted services in Microsoft Azure, including: App Services (Web Apps), Function Apps, CosmosDB, Container Registry, Azure AI Search, Key Vault, and Azure networking and security fundamentals.
  • Demonstrated experience building RAG (Retrieval-Augmented Generation) architectures, including vector indexing, semantic search, and LLM API integration (Azure OpenAI or equivalent).
  • Practical experience with agentic AI frameworks - specifically LangChain and/or LangGraph - including multi-step orchestration, tool use, and stateful agent design.
  • Working knowledge of front-end development using React (Vite-based builds); ability to contribute to and review UI layer work as part of full-stack AI solutions.
  • Ability to collaborate effectively with engineers at varying levels of experience and contribute to a supportive technical team environment.
  • Strong systems thinking: ability to reason through architecture trade-offs, failure modes, security implications, and long-term maintainability before writing a line of code.
  • Clear, confident written and verbal communicator; comfortable presenting technical designs and recommendations to both technical and non-technical audiences.

Preferred:

  • Experience with MCP (Model Context Protocol) or comparable tool-calling and service integration patterns.
  • Familiarity with Node.js as a back-end integration layer.
  • Experience integrating with enterprise platforms such as SharePoint, Confluence, SAP, or similar systems common in large manufacturing or industrial organizations.
  • Exposure to Azure DevOps, CI/CD pipeline configuration, or infrastructure-as-code practices.
  • Experience working within a large, multi-subsidiary or matrixed enterprise environment.
About Us

Legrand is the global specialist in electrical and digital building infrastructures. Its comprehensive offering of solutions for residential, commercial, and datacenter markets makes it a benchmark for customers worldwide.


Legrand, North & Central America offers comprehensive medical, dental, and vision coverage, as well as distinctive benefits like a high employer 401K match, paid time off (PTO) and holiday pay, short-term and long-term disability benefit plans, above-benchmark paid maternity and parental leave, bonus opportunities in accordance with the Company’s incentive plans, paid time off to volunteer, and an active/growing Employee Resource Group network. For more information, visit legrand.us.

Similar Jobs

Yesterday
Remote or Hybrid
286K-392K Annually
Senior level
286K-392K Annually
Senior level
Fintech • Machine Learning • Payments • Software • Financial Services
Designs, develops, deploys, and supports large-scale AI systems, including foundation models, LLM inference, agentic workflows, similarity search, guardrails, and model evaluation. Defines enterprise AI architecture, optimizes model performance, cost, latency, and throughput, establishes AI safety and governance standards, leads multi-year platform initiatives, and mentors senior technical leaders across engineering and research.
Top Skills: Agentic AiAi GovernanceAi ObservabilityAWSAws UltraclustersAzureC#C++CudaFoundation ModelsGoGCPHugging FaceJavaLarge Language ModelsModel EvaluationMulti-Agent WorkflowsPythonPyTorchScalaSimilarity SearchVectordbs
2 Days Ago
In-Office or Remote
120K-215K Annually
Senior level
120K-215K Annually
Senior level
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Designs, develops, deploys, and supports production AI/ML solutions for healthcare operations. Builds scalable machine learning services, data pipelines, cloud applications, and MLOps workflows; implements CI/CD, monitors and optimizes deployed systems, evaluates emerging AI technologies, and collaborates with product, architecture, data science, and engineering teams. The role also mentors junior engineers and contributes to technical standards, code reviews, and architecture decisions.
Top Skills: AWSAzureAzure Machine LearningCi/CdDatabricksGenerative AiGoogle Cloud PlatformLlmMlopsNlpPysparkPythonSnowflakeSQL
3 Days Ago
Remote or Hybrid
286K-392K Annually
Senior level
286K-392K Annually
Senior level
Fintech • Machine Learning • Payments • Software • Financial Services
Leads the architecture, development, deployment, and optimization of large-scale AI systems, including foundation model training, LLM inference, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. Establishes enterprise AI architecture, performance and safety standards, and multi-year platform strategies. Partners across engineering, research, product, and program management while mentoring technical leaders and driving responsible AI adoption.
Top Skills: AWSAws UltraclustersC#C++CudaGoGCPHugging FaceJavaLarge Language ModelsAzureMulti-Agent WorkflowsPythonPyTorchScalaSimilarity SearchVector Databases

What you need to know about the Chicago Tech Scene

With vibrant neighborhoods, great food and more affordable housing than either coast, Chicago might be the most liveable major tech hub. It is the birthplace of modern commodities and futures trading, a national hub for logistics and commerce, and home to the American Medical Association and the American Bar Association. This diverse blend of industry influences has helped Chicago emerge as a major player in verticals like fintech, biotechnology, legal tech, e-commerce and logistics technology. It’s also a major hiring center for tech companies on both coasts.

Key Facts About Chicago Tech

  • Number of Tech Workers: 245,800; 5.2% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: McDonald’s, John Deere, Boeing, Morningstar
  • Key Industries: Artificial intelligence, biotechnology, fintech, software, logistics technology
  • Funding Landscape: $2.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Pritzker Group Venture Capital, Arch Venture Partners, MATH Venture Partners, Jump Capital, Hyde Park Venture Partners
  • Research Centers and Universities: Northwestern University, University of Chicago, University of Illinois Urbana-Champaign, Illinois Institute of Technology, Argonne National Laboratory, Fermi National Accelerator Laboratory

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account